A Study on Value Co-Creation of Franchised Enterprises Driven by Digital Transformation: A Case Study of Tea Beverage Chain ()
1. Introduction
With the advancement of technology and the widespread application of digital technologies such as artificial intelligence (AI), 5G, and virtual reality, the concept of digital transformation has gradually attracted increasing attention from enterprises. Because of the aforementioned digital technologies, traditional organizational operating models and industrial development patterns have changed considerably. Many organizations have begun to implement digital transformation strategies to enhance their efficiency and develop new business models. However, digital transformation involves the transformation of business strategies as well as the improvement of business processes. Enterprises are no longer focused on whether they should undergo digital transformation but rather on how such transformation can be leveraged to create a competitive advantage (Hess et al., 2016).
Regarding the development trends in the franchise market, data published in the 2022 China Catering Franchise Industry White Paper indicate that beverage stores were the business category in China with the highest chain operation rates from 2019 to 2021. The chain operation rate of beverage stores increased from 31.5% in 2019 to 41.8% in 2021, which indicates rapid chain expansion. This growth was associated with strong interest from investment institutions but is also attributable to the retail-oriented characteristics of the beverage industry, which enable rapid standardization and replication. Beverage stores are thus an attractive option for small-scale entrepreneurs. Since 2021, the catering industry’s investment in digitalization has continually increased. For chain restaurants, expansion in terms of stores and business operations creates a need to manage more resources and cope with greater managerial complexity. In the digitalization process, the need for information timeliness, visualization, standardization, and intelligence has increased.
According to the 2023 Commercial Service Industry Development Yearbook, Taiwan region had 2920 franchise headquarters and 121,162 chain stores in 2022. Uni-President Enterprises, PX Mart, and Costco chains all achieved annual revenue exceeding NT$100 billion in that year, and they serve as leading examples of large-scale franchise operations. According to the aforementioned yearbook, franchise brand operators identified the three most critical trends and concerns for 2023-2024 to be precision marketing, digital transformation, and cross-industry collaboration. In response to these trends, franchise headquarters have actively promoted the application of data analytics with the expectation that data utilization and sharing will gradually result in a platform ecosystem centered on the headquarters, with this driving the growth and development of the entire franchise system. Although digital transformation has become a strategic priority for business leaders (Fitzgerald et al., 2014; Hess et al., 2016; Singh & Hess, 2020), empirical research examining how enterprises can successfully achieve such transformation has been relatively limited (Warner & Wäger, 2019). Studies specifically investigating digital transformation at franchise headquarters have been even scarcer. Ooi et al. (2025) suggested that generative AI can assist firms in understanding approaches to new product launches, which is a topic that warrants further investigation.
The platform economy operates through a data-driven service model, meaning that data sharing and application are critical for future development. Digital technologies such as AI, blockchain, and augmented reality can facilitate precision marketing for franchise headquarters while supporting the digital transformation of franchise operators. In addition, service-dominant logic emphasizes that customers are co-creators of value and that organizations can improve their competitive advantage by providing collaborative opportunities and resources that align with customer expectations (Lusch et al., 2007). Digital services can transform how service providers are able to deliver services and can redefine the role of customers within traditional business models. In a digital service environment and on a service platform, customers are both participants and beneficiaries. By using a digital platform to connect stakeholders, organizations can strengthen the mechanisms through which they interact with their customers and more effectively satisfy customers’ needs (Vargo & Lusch, 2016).
In summary, value co-creation between franchise headquarters and franchisees has profound implications for the sustainable operation and development of franchise businesses. Digital transformation and information sharing can provide valuable managerial insights for both franchise headquarters and franchisees. Therefore, how franchise headquarters and franchisees can co-create value through digital transformation must be further investigated. On the basis of the presented research background and motivation, this study sought to answer the following research questions:
1) Why do franchise headquarters initiate digital transformation?
2) How does data sharing influence the marketing activities of franchisees?
3) How does digital transformation drive value co-creation between franchise headquarters and franchisees?
2. Literature Review
2.1. Overview of the Tea Beverage Industry
In this study, the term tea beverage industry refers to the industry in which tea beverage stores use tea leaves as their primary raw material and combine them with various additives and flavoring ingredients to manually prepare beverages with various tastes, flavors, and forms. Tea beverage stores sell freshly made and brewed tea-based drinks. They often introduce various forms of beverages to match seasonal trends and consumer demand, such as smoothies, sparkling drinks, and tea jelly products. They also offer integrated online-offline ordering and product pickup options.
The International Franchise Association defines franchising as an ongoing contractual relationship between a franchisor and a franchisee. Under a franchising agreement, a franchisor is required to provide the franchisee with a unique business privilege along with assistance in personnel training, organizational structure, business management, and product distribution, whereas the franchisee must provide compensation for these offerings. The Japan Franchise Association defines franchising as a contractual relationship in which the franchisor grants franchisees the right to use its trade name, trademarks, and other symbols representing the business as well as its operational know-how, with this enabling the franchisees to sell products under a unified corporate image. In return for these rights, franchisees pay a specified fee to the franchisor and operate their business under the franchisor’s guidance and support. Accordingly, in this study, franchise headquarters are defined within the context of franchising as a business model in which an enterprise (the franchise headquarters) authorizes other independent enterprises (franchise outlets) to utilize its brand, products, technologies, managerial practices, and marketing resources. The franchise headquarters provide comprehensive support services to franchisees with the objective of achieving mutual development and maximizing benefits.
Clarkin and Swavely (2006) reported that cooperative relationships play a critical role within franchise systems and that the relationship between franchise headquarters and franchisees has a strong influence on franchise performance. Lee (2019) proposed four types of franchise headquarters that reflect the diversity of the franchise industry:
1) Management-oriented headquarters, in which the headquarters exercises a moderate to high degree of control over franchisees and adopts an agency or franchising model. Management is established through control of all or part of the ownership of franchise outlets.
2) Supply-oriented headquarters, in which the long-term relationship between the headquarters and franchisees is primarily based on product supply. The core value of the headquarters lies in its joint procurement, centralized distribution, and low to moderate control over franchise outlets, with its role mainly limited to product provision.
3) Store-development-oriented headquarters, in which the primary function of the headquarters is to assist franchisees in establishing stores, with the headquarters playing a role in site selection, store design, traffic flow planning, interior construction, equipment configuration, and procurement of products or raw materials. After a store has been established, the headquarters maintained a low-control relationship, providing only consulting services.
4) Coaching-oriented headquarters, in which the headquarters provides the technical knowledge required for entrepreneurship and store establishment. Their role is limited to teaching operational skills and supplying operation manuals. When the headquarters have granted technical authorization to a franchise outlet, they neither exercise control over nor provide ongoing services to the outlet.
2.2. Digital Transformation
Hess et al. (2016) defined digital transformation as “the use of digital technologies to bring about changes in a firm’s products, organizational structure, or process automation or to transform its business model.”
Fitzgerald et al. (2014) defined digital transformation as “the use of new digital technologies by firms to achieve significant improvements, such as enhancing customer experiences, improving operational processes, or creating new business models.” According to Guenzi and Habel (2020), digital transformation is the process of using digital technologies to modify existing or create new business processes, organizational culture, and customer experiences to meet evolving business and market demands. Singh and Hess (2020) suggested that digital transformation can be regarded as the adoption and use of digital technologies—such as the Internet, mobile technologies, digital platforms, cloud computing, and big data analytics—to improve business activities, including by shortening operational processes, creating new business models, and enhancing customer experiences and loyalty. Bharadwaj et al. (2013) stated that a business’ digital strategy fundamentally influences its business strategy, business processes, resource utilization, core capabilities, and product-service integration as well as the relationships among key partners within its business networks.
On the basis of the aforementioned literature, this study defined digital transformation as the application of digital technologies to improve business activities and extend key partner relationships with the objectives of enhancing customer experiences, improving operational processes, and creating new business models (Bharadwaj et al., 2013; Hess et al., 2016; Singh & Hess, 2020).
Hess et al. (2016) argued that a digital transformation strategy can encompass four major decision dimensions: 1) technology use, which refers to a firm’s ability regarding and approach to exploring and fully utilizing new digital technologies; 2) changes in value creation, which refers to the impact of digital transformation on how firms create value; 3) structural changes, which refers to adjustments in the organizational structures, processes, and skill sets required for the adoption of new technologies; and 4) the financial dimension, which refers to a firm’s ability to provide the financial resources necessary for digital transformation. Ivančić et al. (2019) proposed seven key dimensions of the digital transformation implementation process, namely, strategy, people, organization, customer, ecosystem, technology, and innovation. Correani et al. (2020) developed a framework illustrating how digital transformation can be effectively implemented (Figure 1). They argued that organizations must first define the scope of their desired transformation and then determine how value can be created for customers. In addition, organizations must collect, analyze, and manage data because data constitute a critical element of digital transformation. Through AI, data can be quickly and effectively processed to obtain the information required for decision-making. Organizations must also coordinate their internal digital transformation efforts with external partners as well as support processes that facilitate effective information conversion. The transformed information can then be utilized to support value-creating activities, tasks, and services for customers.
Matt et al. (2015) reported that early adoption of information technology focused on internal IT infrastructure and did not confer considerable innovation benefits. By contrast, digital transformation is a comprehensive transformation
Figure 1. Digital transformation framework (Correani et al., 2020).
process. Notably, when transformation extends beyond organizational boundaries and permeates organizational strategies—including involving overall changes and impacts on products, technologies, services, and business models—managers must ensure it is aligned with corporate objectives. Digital transformation encompasses transformations in both operational strategies—including those related to products, marketing, and processes—and functional-level strategies, including those related to finance, human resources, and information technology. Björkdahl (2020) suggested that data are the most critical resource in a digital transformation process. If an organization is unable to collaborate and share data, it will not be able to obtain the valuable information that data provide. However, data are typically distributed throughout an organization, and only a few firms can manage data in a centralized manner. One means of doing so and, consequently, effectively leveraging the data is to establish a data science team. Organizations can create data lakes that enable organizational members to access and utilize data and thereby generate value for the company. However, governance mechanisms must be established for these teams to ensure effective coordination of internal organizational structures and management processes.
In summary, continually advancing, innovative digital technologies are rapidly transforming the socioeconomic environment and exerting substantial influence on both individual lifestyles and business activities. Continued use of traditional business models results in firms gradually losing their competitive advantage and being replaced by firms employing innovative business models. Consequently, firms are being compelled to rethink their approaches and to adopt digital technologies to establish open and participatory infrastructures, software and hardware systems, and platforms to strengthen customer–product/service connections and customer experiences.
2.3. Value Co-Creation
The main reason why a firm may outperform its competitors and achieve a competitive advantage is an ability to create unique value.
Traditional Schumpeterian innovation emphasizes the creation of value through producer-driven innovation. Press and NY (1996) proposed the concept of the value chain, in which a firm is viewed as a collection of value-adding activities. This concept suggests that value is reflected in the amount customers are willing to pay for a firm’s products or services. Value creation models have gradually evolved toward an open innovation model, in which consumers participate in the value creation process and jointly create value with producers, becoming a crucial source of value creation (Potts & Cunningham, 2008). Vargo and Akaka (2012) argued that value is created through the application of resources in the form of co-creation. Vargo and Lusch (2008) further suggested that customers create value through their participation in the processes of acquiring, using, and disposing of products. Value co-creation enables firms to develop distinctive capabilities through their product development as well as to establish appropriate organizational resources and technological capabilities, and they are thus able to more effectively satisfy customers’ demands for personalized products, services, and experiences and to ultimately gain a competitive advantage (Tanev et al., 2011). Value co-creation with customers can be extended to include stakeholders and stakeholder groups. Therefore, value co-creation can be regarded as a process in which focal firms and other stakeholder groups jointly participate in the design, production, and creation of content and services, thereby collectively influencing the overall creation of value (Osborne et al., 2013).
Research on value co-creation has generally adopted two main perspectives, namely, the marketing and strategic perspectives. Adopting a marketing perspective, Vargo and Lusch (2004) proposed the concept of service-dominant logic, establishing a new marketing paradigm. Service-dominant logic concerns customers’ operant resources, including their knowledge, experience, and capabilities. Value is created when customers utilize their own skills and capabilities to integrate and apply the resources or processes provided by a firm—such as its products, information, and activities—within a particular context to create value for themselves. Tangible products and intangible information and activities are all regarded as services that customers can use to satisfy their needs. Therefore, the service-centered marketing perspective is inherently customer centered and market oriented (Vargo & Lusch, 2004). Consumers’ participation in co-production inevitably influences firms’ production processes. Conversely, firms play a role beyond the traditional one of providers by participating in customers’ value creation processes and becoming value co-creators. Value co-creation occurs when a firm and consumers interact (Vargo & Lusch, 2016).
Regarding the strategic perspective, Prahalad and Ramaswamy (2004) described value co-creation as a process in which active consumer-firm interactions transform value creation into an ongoing dialogue. Through this process, the two parties jointly create unique experiential value. Customers interact through activities provided within a firm’s service network and thereby obtain value generated through resource integration (McColl-Kennedy et al., 2012).
Prahalad and Ramaswamy (2004) proposed the DART model, which consists of four foundational elements that explain how customer-firm interactions facilitate value co-creation: dialogue, access, risk-benefits, and transparency. Dialogue is a critical component of co-creation and represents the deep participation of and interaction between consumers and firms. Both parties are interested in relevant topics and are able and willing to jointly develop and share solutions. Access refers to obtaining the experiential value associated with products and services. Risk-benefits analysis refers to enabling consumers to clearly evaluate and assume the risks and benefits associated with products by providing dialogue, access, and transparency. Finally, transparency refers to information symmetry, with trust serving as the foundation for cooperation and communication between parties.
Cennamo et al. (2020) organized digital transformation methods and value co-creation and value delivery approaches into three major categories of business model transformation, namely, a shift toward data-driven processes, ecosystem formation, and platform market development. Data-driven processes transform organizational operations and internal processes through, for example, monitoring, optimization, and organizational responsiveness. Organizations that utilize data-driven processes are more proactive and efficient and thus may be more competitive. However, data-driven transformations may result in limited creation of value with external firms. Ecosystem formation refers to the use of digital technologies to facilitate collaboration across organizational boundaries, increase firms’ interdependence, promote the sharing of information and resources, generate collective outputs, and develop new value propositions for customers. Creating an ecosystem enhances organizational flexibility and autonomy, but it leads to a need for new governance mechanisms to regulate interorganizational relationships and reward productive contributions. Third, development of platform markets alters competitive dynamics because platform-based data markets transform how value is created and delivered to end customers. Digital platforms can leverage various products’ complementarities to reshape a market’s structure and overall value propositions, expand customers’ choices, and integrate products into comprehensive systems for end users.
In summary, this study adopted the strategic perspective of value co-creation, emphasizing firms’ establishment of value creation contexts and considering the needs and interests of multiple stakeholders. By attracting participation from different stakeholder groups and facilitating meaningful interactions, organizations contribute to the value creation process and engage in collective collaboration with multiple stakeholders. The present study examined the operational strategies of franchise headquarters and the marketing strategies of franchise outlets and investigated relevant value co-creation outcomes from the perspectives of data-driven processes, ecosystem formation, and platform market development (Cennamo et al., 2020; Matt et al., 2015).
3. Research Methodology
3.1. Case Study
Case study research focuses on contextual settings and is able to realistically portray decision-making situations (Eisenhardt & Graebner, 2007).
Through close interaction with practitioners, researchers can investigate the decision-making processes involved in solving actual managerial problems and thereby acquire practical management knowledge (Gibbert et al., 2008). According to Eisenhardt (1989), the case study method involves observing specific environments and conducting in-depth investigations of the various changes that may occur within them. The case study method is particularly useful for examining emerging phenomena at the microlevel and for developing theories (Eisenhardt & Graebner, 2007). When researchers are investigating specific phenomena within real-life contexts and the boundaries between the phenomena and their social context cannot by clearly defined, the case study method enables them to explore why and how the phenomena occur (Yin, 2003). The present study examined how digital transformation drives value co-creation and how data sharing influences firms’ marketing activities, and therefore, it employed the case study method.
This study utilizes a single-case design, treating T Company and its 2023 digital guidance project as a revelatory case (Yin, 2003) to explore the mechanisms of digital-transformation-driven value co-creation. In qualitative inquiry, a case is revelatory if it offers unique access to a phenomenon previously difficult to investigate. While traditional tea beverage franchises are characterized by high fragmentation and low digital density, the 2023 project served as a critical bounded event that integrated disparate information systems into a unified cloud platform. This migration provided an empirical window to capture real-time, two-level interactions between the headquarters’ macro strategies and franchisees’ micro-marketing feedback, thereby unveiling the micro-foundations of value co-creation typically obscured in static, post-hoc studies.
3.2. Case Analysis Framework
3.2.1. Research Framework
This study employed the three major dimensions proposed by Cennamo et al. (2020) for analyzing the impact of digital transformation on business models.
These dimensions represent transformation in terms of data-driven processes, ecosystem formation, and platform market development. Analysis was conducted on two levels, with a focus on the digital transformation of a franchise’s headquarters and how the headquarters assists franchisees in applying data (Matt et al., 2015). The research framework is presented in Figure 2.
Figure 2. Research framework.
3.2.2. Research Scope
1) This study investigated key members of the tea beverage franchise headquarters and franchise outlets who utilized cloud-based solutions for data collection, organization, and analysis. The aim of doing so was to understand how the headquarters and franchise outlets use and share data.
2) Through data analytics, this study examined consumer purchasing behavior, product market intelligence, and the marketing strategies adopted by the headquarters.
3) The scope of this study is primarily limited to the implementation activities in the government-sponsored guidance project in which the case company participated in 2023.
3.3. Data Collection and Analysis
Although secondary data were collected, in-depth interviews were the primary data source in this study.
Babbie (2008) noted that in-depth interviews enable researchers to explore interviewees’ thoughts and perspectives more deeply than they can by using other qualitative research methods, with this enabling a more comprehensive understanding of the research questions under investigation. In this study, in-depth interviews were conducted using the approach proposed by Eisenhardt (1989), which includes identifying a research topic and interview participants, designing interview questions, conducting interviews, transcribing interview data, analyzing the data, and preparing a research report. Accordingly, before the interviews, the researcher identified the research topic and interview participants and developed a semi-structured interview guide. The researcher was also conscious of creating a natural setting in which the interviewer and interviewee could engage in two-way interactions and discussions.
This study used secondary data, interview content, and interview records as the basis for its data analysis. The secondary data included annual business blueprints, internal operational slide decks regarding franchise management, customer relationship management (CRM) system analytical dashboards, official project proposals, competitive landscape analyses, and public press releases regarding the case headquarters. The data were compiled and analyzed through the three-step process suggested by Yin (2003): 1) organization of individual case descriptions and summarization of the major findings from the case, 2) analysis of each case to identify its unique characteristics, and 3) within-case embedded analysis to integrate the findings and develop the basis for conclusions and recommendations. An interview guide and interview questions were developed on the basis of the research framework. Following the completion of the interviews, the recorded interview data were transcribed verbatim and integrated with secondary data to identify the context and findings of the case study.
Eight interviewees participated in this study. Through purposive sampling, key informants were selected based on their firsthand involvement in the 2023 digital guidance project, subject to two strict criteria: 1) headquarters informants had to occupy executive or managerial positions directing digital strategy or IT deployment, and 2) franchisee informants required a minimum of two years of operational tenure alongside full migration to the cloud platform during the project. They were senior executives from the case franchise headquarters (M1 and M2), marketing managers (M3 and M4), franchise store owners and managers (F1 and F2), and information service providers (IT1 and IT2). The interviews were conducted between January and April 2024. To accommodate geographical dispersion, interviews were held either face-to-face at the headquarters/franchise stores (n = 5) or via synchronous video conferencing (n = 3). Individual sessions averaged 78 minutes (ranging from 60 to 95 minutes), all of which were audio-recorded with explicit consent and transcribed verbatim. Methodological rigor was maintained by applying Braun and Clarke’s (2006) six-phase thematic analysis framework to both primary transcripts and secondary documents, progressing through Familiarization, Generating Initial Codes, Searching for Themes, Reviewing Themes, Defining and Naming Themes, and Producing the Report. To ensure trustworthiness (Guba & Lincoln, 1994) and mitigate subjective bias, a dual-coder protocol was deployed; the initial inter-coder reliability check yielded a robust Cohen’s Kappa of 0.84.
Grounded in qualitative methodology, sample adequacy is determined by data saturation—the threshold where further data collection yields redundant information (Hennink & Kaiser, 2022). Literature indicates that within a homogeneous, bounded single case, core themes can surface in six to twelve interviews (Guest et al., 2006). In this study, because all informants shared a single corporate framework and underwent the identical 2023 digital transformation mandate, their operational narratives converged rapidly. Conceptual redundancy regarding data-sharing mechanisms and precision marketing feedback became evident by the sixth and seventh interviews. The eighth interview captured no novel properties or dimensional variations, demonstrating that theoretical saturation was robustly achieved to ensure the trustworthiness of our framework.
3.4. Case Company Profile
T Beverage Company developed from a tea merchant company that was established in 1907 and has become one of Taiwan region’s leading enterprises specializing in traditionally brewed tea. In an effort to dispel the perception that beverage stands in Taiwan region used low-grade tea leaves, the company’s founder, Chairman Yang, entered the iced tea market in 2006 and began to serve premium high-mountain oolong tea, which at the time cost nearly NT$1000 per jin. The use of high-quality tea leaves in beverage preparation was a new business concept in Taiwan region’s iced tea industry.
Since its entry into the market in 2006, T Beverage Company has been committed to expanding both domestically and internationally. It established its operational headquarters in Beitun District, Taichung City. Originally a tea factory, the company operates under a vertically integrated business model encompassing tea production, processing, and retailing. It manages its own beverage brand and is known for its proprietary rapid-freezing technology, with which fresh fruit can be preserved at −200˚C.
The company’s main business is the sale of takeaway tea beverages. Its operations include supplying raw materials and fresh fruit ingredients to franchise stores as well as providing franchise business consultation and support services. T Beverage Company applies HACCP and ISO 9001 certification standards for tea production to its beverage operations. The company provides practical guidance and comprehensive technology transfer to ensure strong collaboration between the headquarters and franchisees, which enables it to effectively manage the brand overall. Adhering to a principle of steady expansion, the company assists franchisees in profiting from the brand’s reputation and business benefits.
Recently, T Beverage Company successfully launched the “108 Tea King” series of products, with the series production supervised by a tea factory that has received three-star recognition from the International Taste & Quality Institute. This product line has become one of the company’s flagship offerings. In addition, the company continually introduces new beverages and engages in co-branding marketing campaigns with other brands. It maintains a stable consumer base, and its customers have strong brand loyalty.
As of the end of 2023, T Beverage Company operated 150 chain stores in Taiwan region and 15 franchise stores in overseas markets. The number of newly opened stores and the volume of logistics sales for the company have exhibited steady annual growth. Chairman Yang envisions that the company will promote Eastern tea culture globally and develop into a world-class leader in the tea and beverage industry.
4. Research Findings and Discussion
4.1. Drivers of Digital Transformation at Franchise Headquarters
In analyzing the data from the in-depth interviews, this study identified three primary reasons why the franchise headquarters felt a need to enable data sharing as a means of addressing operational challenges. First, the consumer data held by the headquarters and franchisees were fragmented and isolated, and no mechanism was present for integrating the data. Second, the operational and consumer data available to the headquarters were scattered across different systems, and therefore, marketing personnel with limited analytical experience had difficulty in effectively screening and analyzing the data. Third, because of their insufficient experience and limited access to clear and comprehensive data, the marketing personnel at the headquarters were often unable to develop marketing content tailored to the needs of individual franchise outlets (Table 1).
Table 1. Problems that the franchise headquarters and franchisees expect to address through a data platform.
Question |
Description |
Reason |
1 |
Inability to effectively expand customer segments and develop new products and services. |
Operational and consumer data at the headquarters are fragmented and isolated; no integration mechanism has been established. |
2 |
Inability to respond promptly to and meet the actual needs of members. |
The operational and consumer data available to the headquarters are scattered and fragmented. In addition, marketing personnel often lack sufficient experience in data screening and analysis. |
3 |
Inability to integrate technology-driven marketing efforts, resulting in wasted marketing resources. |
Because of limited experience and insufficient data visibility, marketing personnel at the headquarters are unable to develop appropriate marketing content tailored to each target audience. |
As one marketing manager (M3) explained,
At present, the company’s operational and consumer data are distributed across multiple databases, and therefore, the data are fragmented and scattered. Consequently, we can’t effectively analyze individual stores’ revenue performance, product sales, membership management, or consumer behavior.
A senior executive at the headquarters (M1) further stated,
The primary reason the company is seeking to undertake digital transformation is so it can use data analytics to scientifically identify what new products or services should be developed so that the company can stay ahead of competitors. We also hope to continually introduce innovative and signature products within the highly competitive tea beverage industry to encourage more customers to join our membership program.
An information service provider (IT1) noted, “T Company is constrained by insufficient internal operational and consumer data. If consumer data are not effectively integrated, identifying trends and directions within the consumer market becomes difficult.”
4.2. Cloud Services and Data Sharing
T Company established a data analytics and sharing platform to enable data analysis and sharing between the franchise headquarters and individual franchisees and thereby improve decision-making efficiency and obtain organizational insights at the headquarters. The primary function of the platform is to collect, organize, and analyze data from franchise outlets to ensure the headquarters has access to accurate information and can obtain comprehensive insights. The headquarters can use the data to optimize their operations and development strategies. The cloud services and data-sharing practices are described in the following:
1) Headquarters Data Collection and Integration: The platform can collect various types of data from individual franchise outlets, including sales data, inventory data, and customer feedback. These data are integrated and stored in a centralized database to facilitate analysis and comparison. At the headquarters, the data analysis performed includes analysis of the total number of franchise members, the gender and age distributions of these members, the overall best-selling products, membership rankings, and membership segmentation.
2) Data Sharing Between the Headquarters and Franchise Outlets: The data platform facilitates data sharing and collaboration between the headquarters and franchise system. This study discovered that the headquarters uses a store management application to provide valuable membership insights to franchisees, helping them improve their business operations. Additionally, franchisees can provide suggestions and feedback to the headquarters. The data the headquarters share with the franchise outlets include the total number of members at each franchise outlet, the gender and age distributions of members, outlet-specific membership numbers, and sales rankings of stores within the same geographic area.
3) Data-Sharing Mechanism Provided by the Headquarters: The platform presents the results of data analysis through intuitive and easy-to-understand visualizations, enabling franchisees and decision-makers at the headquarters to quickly understand the meanings and trends behind the data; additional interpretation from consultants or data scientists is unnecessary.
4) Cloud Services and Franchise Data Sharing Provided by the Headquarters
a) Cloud Solution I: Membership Data Integration and Sharing Platform. The headquarters consolidates and analyzes fragmented customer information and provides the results of these analyses to franchisees through a cloud-based data integration and sharing platform. With this platform, individual franchise outlets can understand the profiles and characteristics of their members (Figure 3).
b) Cloud Solution II: AI-Based Membership Tagging and Segmentation System. On the basis of shared data, franchise outlets submit a request for a differentiated marketing campaign to the headquarters. The headquarters then utilizes an AI-powered tagging and segmentation system to identify and select an appropriate target audience for promotional activities.
Figure 3. Cloud services and data sharing between the franchise headquarters and franchise outlets.
c) Cloud Solution III: Generative AI Marketing Content Advisory System. On the basis of the preferences of the selected target audience, the headquarters employs generative AI technology to generate marketing content and intelligent recommendations; this improves marketing efficiency and increases coupon conversion rates.
This study’s results are consistent with the argument of Björkdahl (2020), who stated that data are the most critical resource in a digital transformation process. Data sharing and collaboration enable franchise headquarters and franchisees to obtain valuable information, which stimulates business growth.
4.3. Data-Driven Value Co-Creation
1) Precision Marketing Involving the Headquarters and Franchise Outlets
Step 1: Aligning with Headquarters’ Operational Strategies and Leveraging Consumer Data
When planning a precision marketing program, marketing personnel at the headquarters first review the key strategic marketing priorities of the company, including considering discount strategies, seasonal products, flagship product promotions, and promotional campaigns. On the basis of these priorities and database analytics results, they develop preliminary concepts and themes for precision marketing initiatives.
As a senior executive at the headquarters (M2) stated,
After internal marketing discussions, the headquarters develops marketing campaigns based on seasonal products, corporate strategies, and flagship products. In this stage, for example, the beverage product “Hawthorn 108 (Tea King)” could be selected as the primary promotional target.
Additionally, a marketing manager (M4) noted, “We first review the rankings of the 10 best-selling products. We collect consumer data and utilize marketing tools such as online advertising and in-store promotions to achieve product promotion objectives.”
Step 2: Identifying Target Customer Segments
On the basis of the attributes of promotional products, such as their pricing, target customer groups are identified by consulting consumer characteristics and recency-frequency-monetary value (RFM) segmentation analytics. Customer preferences and predictive analyses of related products are employed to determine the most appropriate target audience. In this study, an information service provider (IT2) indicated that the marketing personnel at T Company headquarters used RFM segmentation analytics to develop a precision marketing program for the target product “Hawthorn 108 (Tea King)” and selected Grade A members (from the A, B, and C membership classes) as the target audience.
Step 3: Precision Marketing and Customer Acquisition
Generative AI suggests promotional content for addressing the identified target audience. Marketing personnel may either directly use the AI-generated content or make some modifications to it before publishing and delivering the targeted promotional messages.
Step 4: Optimization of Subsequent Marketing Programs
The headquarters provides franchise outlets with performance reports, the results of promotional campaigns, and analyses of historical operational and marketing data. These insights serve as the basis for improving future marketing activities and assisting franchisees in planning promotional initiatives.
2) Adjustments to Marketing Strategies by the Headquarters and Franchisees
The headquarters adjusts marketing strategies on the basis of both subjective and objective analyses of the franchise system.
Regarding the subjective perspective, one marketing manager (M3) stated,
The headquarters reviews the sales performance of newly launched products and evaluates their market performance by examining sales data collected by the company. We also assess the effectiveness of previous marketing strategies and compare promotional outcomes with actual purchase volumes.
Regarding the objective perspective, the headquarters considers sales performance and consumer feedback collected from individual outlets when adjusting marketing strategies. A senior executive (M2) explained,
We review the Top 10 products by looking at store sales reports. If “Hawthorn 108 (Tea King)” is among the Top 10 products in more than half of the stores, the headquarters may increase promotional activities and marketing campaigns for that product to stimulate demand. In addition, the product development department evaluates seasonal factors, current events, and market demand on a monthly basis to determine marketing activities for the following month or quarter. These sales reports provide a strong basis for strategic marketing adjustments.
Furthermore, a franchise outlet manager (F1) commented,
In the past, marketing campaigns were primarily planned and directed by the headquarters, and the needs and local contexts of individual stores were not adequately considered. For example, customer characteristics differ significantly between outlets located near office buildings, residential neighborhoods, and night markets. These customer groups have distinct needs and preferences.
Store managers can review the top-selling products through store sales reports, develop outlet-specific promotional strategies, and adjust procurement volumes for related raw materials accordingly. Such actions enhance sales performance and reduce inventory costs.
3) Data-Driven Value Co-Creation Between the Headquarters and Franchise Outlets
From the perspective of the headquarters, data-driven value co-creation involves the following. Grounded in the service-dominant logic paradigm (Vargo & Lusch, 2004, 2016), value co-creation within a franchise context is conceptualized not as a unidirectional value delivery from headquarters to individual stores, but as an interactive process. To ensure empirical objectivity rather than relying on subjective evaluation, this study defines the precision marketing success rate using the objective metric of targeted campaign conversion rate captured by the CRM system. Furthermore, customer satisfaction is operationalized as a transactional evaluation measured via the franchise brand’s official mobile application, while the A/B/C membership grading system serves as the strategic segmentation framework embedded within the case enterprise’s unified CRM platform.
a) Understanding Membership Profiles and Structures
Through automated member tagging and segmentation, the system enables the headquarters to implement more personalized marketing strategies. On the basis of different customer groups and labels, the headquarters can provide franchise outlets with targeted product recommendations, discounts, and promotional campaigns, thereby increasing conversion rates and customer satisfaction.
b) Enhancing Data Integration and Sharing Capabilities
The three cloud services developed by the company provide solutions for integrating and sharing membership data. These services address data fragmentation across different systems and channels, establish centralized membership databases, and facilitate effective data utilization.
c) Developing Personalized Marketing Strategies
The three cloud services provide strategic recommendations based on customers’ characteristics and behavioral patterns. This enables the headquarters to offer products and services that directly meet customer needs. In this case, customer segmentation is based on the RFM model. Following machine-learning analysis, the system automatically classifies members into three levels and eight segments, and different marketing strategies are available for each segment.
Grade A customers are high-value and high-potential customer groups. Grade B customers represent key retention, maintenance, and development groups. Grade C customers represent general retention and maintenance groups.
For example, high-value Grade A customers are regarded as VIP customers. The system recommends that they be given timely rewards, that their sense of exclusivity be strengthened, and that they be encouraged to provide word-of-mouth referrals. High-potential Grade A customers are customers whose patronage could be increased considerably, and the system recommends that their service experiences be closely monitored to ensure they are highly satisfied. Ultimately, the headquarters reviews these recommendations, formulates final marketing plans, conducts targeted promotions, and tracks the promotions’ performance to enable subsequent refinement.
From the perspective of franchisees, data-driven value co-creation involves the following:
1) Supporting Inventory Management and Sales Forecasting
By using data provided by the headquarters, franchise outlets can access automatically generated information on members, including their gender, age, birthday, visited outlets, redeemed outlets, purchased products, redeemed reward items, utilized coupons, consumption periods, redemption periods, and participation in promotional activities. These data can support sales forecasting and provide valuable references for inventory management and procurement decisions.
2) Facilitating Data Sharing Among Franchise Outlets
The data platform promotes data sharing among franchise outlets, enabling each outlet to access membership information relevant to its operations. Such sharing helps stores better understand customer profiles, attributes, and preferences, facilitating cross-store marketing activities and enhancing customer convenience and service experiences across different locations.
From the perspective of headquarters employees, data-driven value co-creation involves the following:
3) Improving Work Efficiency and Reducing Costs
Obtaining generative AI marketing content considerably reduces the time demands on marketing personnel, enhances competitiveness in rapidly changing markets, enables faster responses to market demands, and improves overall marketing efficiency.
4) Enhancing Personalized Marketing Content
The AI marketing content advisory system provides personalized recommendations and optimization suggestions on the basis of an audience’s characteristics, preferences, and behaviors. These suggestions can help marketing messages more effectively meet the target audience’s needs, improving communication effectiveness and response rates.
In addition, this study noted that AI generation of marketing content exerts multiple influences on the marketing strategies of the tea beverage franchise system; it provides data-driven insights, improves work efficiency, enhances content quality, and enables rapid responses to market changes.
First, AI provides data-driven insights by analyzing marketing outcomes and identifying the most effective promotional content, thereby supporting continual optimization of marketing strategies. Data analytics functions also facilitate the identification of market trends and consumer preferences, resulting in more scientific and accurate marketing decisions.
Second, generative AI considerably improves work efficiency. The examined case study revealed that AI can rapidly generate large quantities of high-quality marketing content, substantially reducing the time and cost associated with manual content creation. Marketing teams therefore have more resources available to allocate to strategic planning and creative development.
Third, AI produces high-quality content by analyzing successful marketing content and historical marketing data to generate promotional messages aligned with the headquarters’ marketing strategies. This contributes to higher click-through and conversion rates. AI can also detect and correct grammatical errors and awkward sentence structures, ensuring consistency in content quality.
Fourth, generative AI enables organizations to respond quickly to market changes by generating content that reflects trends and events, allowing brands to capitalize on emerging marketing opportunities.
The franchisee interviewees generally agreed that AI-generated advertising content has enhanced employees’ marketing planning capability. This finding is consistent with that of Chaisatitkul et al. (2024), who reported that consumers have positive perceptions of content created by generative AI.
Overall, the application of generative AI in marketing content creation improves efficiency, accuracy, and innovation in marketing decision-making, rendering headquarters’ marketing activities more flexible and competitive.
To substantiate the outcomes of the digital-transformation-driven value co-creation framework, this section reports the descriptive operational improvements recorded by the case enterprise’s unified CRM and enterprise resource planning (ERP) systems. It is critical to note that these metrics are presented strictly as descriptive platform tracking data and historical aggregates rather than inferential statistical findings; no formal inferential hypothesis or significance testing was executed. The unit of analysis and specific observation periods are between January 1 to October 31, 2024. The tangible outcomes of value co-creation can be observed in several areas:
1) Growth in headquarters revenue: During the project implementation period, the headquarters’ revenue increased from NT$120 million to more than NT$143 million.
2) Improvement in service efficiency: Data analytics enabled the headquarters and franchise system to more effectively understand their product and service performance, resulting in optimized product design and service processes. Five new products were successfully launched.
3) Growth in brand membership: Membership increased from 82,010 at the beginning of the project to 160,370 by the end of the project.
4) Revenue growth across the franchise system: Data analytics enhanced understanding of market trends and customer needs, leading to the creation of more effective marketing and sales strategies. Revenue across the franchise system increased by more than NT$32 million.
5) Improved precision in marketing strategies: During the project period, the success rate of promotional recommendation campaigns was 21.59%, compared with the preproject rate of 14.3%.
6) Enhanced customer experience value: Data analytics enabled the firm to better understand customer needs and preferences and provide more targeted and personalized products and services. Customer satisfaction increased from 82% to 90%.
These findings are consistent with the value co-creation dimensions proposed by Prahalad and Ramaswamy (2004). First, dialogue was facilitated through the integration of franchise headquarters, franchise outlets, and a consumer data-sharing platform, enabling collaborative problem solving. Second, regarding access, customers could have innovative experiences through participation in data-enabled product launches and promotional activities. Third, risk–benefits were evaluated through dialogue, access, and transparency, enabling consumers to make informed assessments of products and associated risks and benefits. Fourth, transparency was enhanced through the data platform, which increased the visibility of customer information and store performance across the franchise system. Information symmetry resulted in greater trust between the headquarters and franchise outlets and promoted long-term collaborative relationships.
In summary, the tea beverage franchise headquarters has increasingly recognized the necessity of digital transformation. By integrating strategic objectives with digital transformation initiatives, the headquarters has promoted the digital transformation of its entire franchise system and achieved value co-creation outcomes. Through data-driven processes, the franchise headquarters connect information systems across franchise outlets and collects consumer data from individual stores. By analyzing customer data and implementing precision marketing, the headquarters help franchise outlets improve sales performance and customer loyalty while sharing customer profiles and market intelligence. Furthermore, by combining strategic objectives, flagship products, and consumer data with generative AI marketing content, the headquarters help franchisees improve their marketing efficiency and strengthen collaborative relationships within the franchise system. These data-driven processes involve the headquarters, franchisees, and customers working collectively toward strategic objectives through the collection, organization, and application of data. Through the data, new products, services, and promotional activities can be developed in response to seasonal changes and market demands, achieving value co-creation. Value co-creation outcomes can be evaluated using the DART framework to assess whether all stakeholders benefit from the collaboration and are motivated to continue collaborating. The present study proposed a conceptual framework illustrating how digital transformation drives value co-creation in franchise enterprises (Figure 4).
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Figure 4. Value co-creation framework driven by digital transformation in franchise enterprises.
5. Conclusion
The Chinese-speaking world has a unique tea beverage culture, and the tea beverage market, has created enormous business opportunities and fostered the emergence of numerous tea beverage enterprises. The current ready-to-drink tea market is a highly competitive international business arena. The application of data analytics and digital transformation by franchises is undoubtedly contributing to the international competitiveness of numerous tea beverage brands. Through data sharing, both franchise headquarters and franchisees can improve their market positioning and marketing efficiency with precision marketing, establishing the foundation of a franchise platform ecosystem. In addition, these efforts can help increase customer loyalty and enhance the market competitiveness of franchisees.
This study proposes a two-level analytical framework in which digital transformation drives both the operational strategies of franchise headquarters and the functional strategies of franchise outlets. This framework may provide a useful reference for future studies of the franchise industry. Furthermore, by examining how franchise headquarters utilize digital technologies such as cloud services to implement data analytics, share data, operate franchise ecosystems, and create and deliver customer value, this study analyzed the activities and outcomes of value co-creation. The empirical findings reveal that digital transformation enhances the overall profitability of franchise headquarters.
5.1. Practical Applications and Managerial Implications
1) Franchise industries are recommended to adopt a data-driven approach to promote value co-creation among franchise outlets. The case company, T Company, is committed to achieving effective consumer data analysis and application and has actively introduced service innovations and new products to provide new experiential value and pricing benefits to members. These efforts have simultaneously increased the revenue of its takeout and delivery tea beverage franchise system and improved the competitive advantage of the franchise network.
2) Data analysis and sharing through a data platform can facilitate the optimization of managerial decision-making at headquarters and support the development of localized and precision marketing programs. This differs from traditional marketing knowledge and know-how, which often remain tacit and embedded in the minds of managers and therefore cannot be easily shared.
3) When headquarters enable data sharing, franchisees can gain a concrete understanding of the meaning of the data and behavioral patterns of consumers. Consequently, marketing activities can be implemented on the basis of marketing science and evidence-based decision-making. Furthermore, franchise outlet personnel can utilize the data provided by headquarters to interpret and communicate the brand’s culture and values while simultaneously translating data-driven insights into enhanced customer brand experiences.
4) Most franchise systems operate within the commercial service sector, in which personnel constitute the core element of service delivery. To enhance competitiveness, franchise brands require not only owners and executives with the vision and insight necessary for digital transformation but also employees who are willing and able to contribute to organizational transformation efforts. Through digital empowerment, organizations can strengthen employees’ digital awareness and analytical capabilities, thereby supporting the successful implementation of digital transformation initiatives.
5.2. Research Limitations and Future Research
This study analyzed a single case. Therefore, the generalizability of the findings and results is limited. In addition, the objectivity of the interview data may have been relatively low. Future studies may examine a larger number of cases to enhance the objectivity and rigor of the research findings.
Future research may further investigate several related topics. For example, researchers may explore how generative AI tools can facilitate the development of dynamic webpages that adapt on the basis of customer segmentation and geographic location. In addition, comparative studies may be conducted to examine differences in digital transformation models between various franchise industries.